Search Results for "python data analysis" - Page 7
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485 projects for "python data analysis" with 2 filters applied:
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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NanoH5 (tsl2nano)
java bean / database driven zero code application framework
NanoH5 (or FullRelation) is a fullstack UI implementation framework providing a model driven design (MDA). Build a complete html5 application through a given class- or database-model without coding (coding APIs are available). -
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myScite
The allRound pocket sized CodeEditor.
.... -- Features -- - Full MinGW and GTK SDKs Autocomplete.(190+) - Do system scripting (bash, applescript, cmd, powershell, perl, j/vbscript, awk) - Examine all sorts of data files (sql, regedit, mib, xml, yaml, json, vcard ...) - Review difference and patch files - Create makefiles (gnu make / cmake) - Edit html, css and config files (with calltips) - Describe circuits in vhdl and spice. ... - And finally; read & write source code: - [ Syntax highlighted ] - go, vala, pike, swift, flash, ch, rust - [ Calltip assisted ] - c/cpp11, js&jQuery, python, php, ruby, lua, c#, java, perl --Others-- - Restructured config files with inline docs - Scriptable via lua Extension... -
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Emjysoft Gestion Locative Connector
Open-source plugin connector for Emjysoft Gestion Locative v22+
...KEY FEATURES: - Send rent notices, receipts, and certificates to external systems - Support for HTTP POST (with basic authentication) and EXE integration - JSON-based data format with 128-bit UUIDs - Base64-encoded document content - PHP and Python integration examples included - MIT License - free to use and modify SUPPORTED DOCUMENTS: - Rent calls/notices - Rent receipts - Payment reminders - Rent revisions - Service charge adjustments - Payment schedules - Certificate requests -
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Ring
Simple and flexible programming language for applications development
The Ring is a practical general-purpose multi-paradigm language. The supported programming paradigms are imperative, procedural, object-oriented, declarative using nested structures, functional, meta programming and natural programming. The language is portable (MS-DOS, Windows, Linux, macOS, Android, WebAssembly, Microcontrollers, etc.) and can be used to create Console, GUI, Web, Games and Mobile applications. The language is designed to be simple, small and flexible. Ring is... -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,... -
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Glumpy
Python+Numpy+OpenGL, scalable and beautiful scientific visualization
Glumpy is a Python library that simplifies the development of high-performance, interactive OpenGL visualizations. It abstracts complex OpenGL tasks into Pythonic constructs, making it easier for scientists, artists, and developers to harness the power of the GPU for real-time rendering and data visualization. Glumpy is particularly well-suited for rapid prototyping of graphical applications, and its integration with NumPy and shader programming makes it a powerful tool for both research and creative exploration. -
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Statistical Rethinking 2023
Statistical Rethinking Course for Jan-Mar 2023
...It continues to provide scripts for lectures and tutorials, while integrating refinements to examples, notation, and computational workflows introduced that year. Compared with 2022, some models are rewritten for clarity, and teaching materials reflect refinements in McElreath’s evolving presentation of Bayesian data analysis. Students following the 2023 lecture videos use this repository as their coding reference. There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting. -
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Gait Tracking With x-IMU
Foot tracking algorithm demonstrated in Seb Madgwick's 3D Tracking
...The method performs dead reckoning to integrate foot motion and corrects for drift at each foot strike (when the foot touches the ground) to reset error accumulation. The algorithm was part of gait analysis research, estimating foot trajectories in 3D over time. The repo is marked “no longer maintained,” and has been superseded by newer versions of Gait-Tracking. Capability to compare walking trajectories in experiments. Integration of IMU data (accelerometer + gyroscope). -
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databooks
A CLI tool to reduce the friction between data scientists
databooks is a package to ease the collaboration between data scientists using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and resolution of git conflicts when encountered. Simply specify the paths for notebook files to remove metadata. By doing so, we can already avoid many of the conflicts. Specify the paths for notebook files with conflicts to be fixed. Then, databooks finds the source notebooks that caused the conflicts and compares them (so no... -
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learn2learn
A PyTorch Library for Meta-learning Research
Learn2Learn is a PyTorch-based library focused on meta-learning and few-shot learning research. It provides reusable components and meta-learning algorithms, making it easier to build, train, and evaluate models that can quickly adapt to new tasks with minimal data. Learn2Learn is widely used in research for tasks such as few-shot classification, reinforcement learning, and optimization. -
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CARTOframes
CARTO Python package for data scientists
A Python package for integrating CARTO maps, analysis, and data services into data science workflows. Python data analysis workflows often rely on the de facto standards pandas and Jupyter notebooks. Integrating CARTO into this workflow saves data scientists time and energy by not having to export datasets as files or retain multiple copies of the data. -
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iJEPA
Official codebase for I-JEPA
i-JEPA (Image Joint-Embedding Predictive Architecture) is a self-supervised learning framework that predicts missing high-level representations rather than reconstructing pixels. A context encoder sees visible regions of an image and predicts target embeddings for masked regions produced by a slowly updated target encoder, focusing learning on semantics instead of texture. This objective sidesteps generative pixel losses and avoids heavy negative sampling, producing features that transfer... -
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The Related Values Processing Framework helps the integration of Process Control Data Historian Systems.
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A general purpose source code indexer and cross-referencer that provides web-based browsing of source code with links to the definition and usage of any identifier. Supports multiple languages. Up-to-date information in http://lxr.sourceforge.net
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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Cinemagoer
Python package to retrieve and manage data of the IMDb
Cinemagoer is a Python package useful to retrieve and manage the data of the IMDb movie database about movies, people, characters and companies. Platform-independent, it can retrieve data from both the IMDb's web server and a local copy of the whole db. -
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Data science blogs
A curated list of data science blogs
Data Science Blogs is a curated repository that aggregates a wide range of high-quality blogs and resources related to data science, machine learning, and analytics into a single organized collection. It serves as a discovery platform for practitioners, researchers, and learners who want to stay updated with industry trends, techniques, and insights without manually searching for reliable sources. The repository includes links to personal blogs, professional publications, and educational... -
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quantitative
Quantized transactions python3
...The README and associated lessons walk the user through implementing algorithms, likely covering data handling, backtesting, and maybe simple trading logic. As an open-source educational resource, it’s designed for Python users interested in automatic trading, algorithmic strategies, and financial data analysis. -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. -
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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Name-That-Hash
Identify MD5, SHA256 and 300+ other hashes
...One of its core ideas is popularity-aware ranking: when you feed in a hash, it prioritizes likely real-world types such as NTLM over obscure ones like Skype hashes, instead of treating them equally. The tool provides concise “hash summaries” that explain where a given hash format is commonly used, helping users decide how to proceed with cracking or further analysis. Name-That-Hash is accessible via a Python CLI (nth) and also exposes an API and JSON output, making it easy to plug into other tools or workflows, and there is also a web app that requires no local installation. -
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OpenCensus Libraries for Go
A stats collection and distributed tracing framework
OpenCensus and OpenTracing have merged to form OpenTelemetry, which serves as the next major version of OpenCensus and OpenTracing. OpenCensus is a set of libraries for various languages that allow you to collect application metrics and distributed traces, then transfer the data to a backend of your choice in real time. This data can be analyzed by developers and admins to understand the health of the application and debug problems.
